A spatiotemporal control method at isolated intersections under mixed-autonomy traffic conditions

With the introduction of connected and automated vehicles (CAVs), the integrated control of traffic signals, lane assignments, and vehicle trajectories becomes feasible, offering notable benefits for enhancing intersection operations. However, during the prolonged transition to an entirely CAV environment, how to fully leverage the advantage of CAVs while considering the characteristics of human-driven vehicles remains a huge challenge. To address this challenge, this paper proposes a joint optimization method for spatiotemporal resources at isolated intersections under mixed-autonomy traffic conditions. Initially, the lane assignment optimization problem is modeled as a mixed integer linear program model to maximize the reserve capacity. Subsequently, the signal-vehicle coupled control is formulated as a dynamic programming model with the objective of reducing vehicle travel time. Additionally, criteria are established to assess the need for re-optimizing lane assignments. Simulations validate the superiority of the proposed control method over adaptive control in terms of traffic efficiency and intersection capacity amid substantial traffic demand fluctuations. Sensitivity analyses reveal that the proposed control method can yield higher benefits under medium traffic demand levels. Furthermore, the proposed algorithm exhibits no significant sensitivity to the CAV market adoption rate, suggesting its applicability throughout the CAV adoption process.     

Increasing Signalized Intersection Capacity with Unconventional Use of Special Width Approach Lanes

Heavy traffic volume coupled with insufficient capacity due to limited space cause most of traffic congestion at urban signalized intersections. This article presents an innovative design to increase the capacity of heavily congested intersections by using the special width approach lane (SWAL), which consists of two narrow approach lanes that are dynamically utilized by either two passenger cars or a heavy vehicle (e.g., buses or trucks) depending on the composition of traffic. The impact of the SWAL on the saturation flow rate is quantified and validated, followed by an optimization model for best geometric layout and signal timing design with the presence of the SWAL. The optimization model is formulated as a mixed‐integer‐linear‐program for intersection capacity maximization which can be efficiently solved by the standard branch‐and‐bound technique. Results of extensive numerical analyses and case studies show the effectiveness of SWAL to increase intersection capacity, indicating its promising application at intersections with very limited space that prevents the addition of separate lanes.     

道路平面交叉口次路远引几何参数设置及通行效率研究

次要车流的左转和直行对交叉口车辆运行影响较大,特别是主路交通流量较大时尤为明显,通过次要道路车流远引的方式可以减少交叉口车辆冲突,有利于提高交叉口运行效率。分析了平面交叉口次路远引适用条件与车流组织方法,以延误最小为目标,构建了远引回转车流掉头位置、远引车辆掉头排队车道长度、远引掉头处开口长度与宽度等关键几何参数计算模型,提出了次路远引交叉口延误和通行能力等计算方法。结合实例验证了上述方法的可行性,仿真显示,在一定条件下平面交叉口次路远引可有效减少信号相位数和车辆平均延误,表明了平面交叉口次路远引的交通组织方法对优化城市道路交叉口设计有较好的应用价值。     

Two‐Dimensional Simulation of Turning Behavior in Potential Conflict Area of Mixed‐Flow Intersections

The potential conflict area of intersection is the space where conflicting traffic flows pass through in the same signal phase. At this area, turning vehicles interact with most traffic flows, which introduce complex features including variation of trajectories and shared‐priority phenomenon. The traditional one‐dimensional simulation oversimplifies these features with lane‐based assumption. This study integrates the modified social force model with behavior decision and movement constraints to reproduce the two‐dimensional turning process. The method is framed into a three‐layered mathematical model. First, the decision layer dynamically makes decision for turning patterns. Then the operation layer uses the modified social force model to initially generate vehicle movements. Finally, the constraint layer modifies the vehicular motion with vehicle dynamics constraints, boundary of intersection and the collision avoidance rule. The proposed model is validated using trajectories of left‐turn vehicles at a real‐world mixed‐flow intersection with nonprotected signal phases, resulting in a more realistic simulation than previous methods. The distributions of decision points and travel time in simulation are compared with the empirical data in statistics. Moreover, the spatial distribution of simulated trajectories is also satisfactory.     

Passing Rates to Measure Relaxation and Impact of Lane‐Changing in Congestion

Abstract: Passing rate measurements of backward‐moving kinematic waves in congestion are applied to quantify two traffic features; a relaxation phenomenon of vehicle lane‐changing and impact of lane‐changing in traffic streams after the relaxation process is complete. The relaxation phenomenon occurs when either a lane‐changer or its immediate follower accepts a short spacing upon insertion and gradually resumes a larger spacing. A simple existing model describes this process with few observable parameters. In this study, the existing model is reformulated to estimate its parameter using passing rate measurements. Calibration results based on vehicle trajectories from two freeway locations indicate that the revised relaxation model matches the observation well. The results also indicate that the relaxation occurs in about 15 seconds and that the shoulder lane exhibits a longer relaxation duration. The passing rate measurements were also employed to quantify the postrelaxation impact of multiple lane‐changing maneuvers within a platoon of 10 or more vehicles in queued traffic stream. The analysis of the same data sets shows that lane‐changing activities do not induce a long‐term change in traffic states; traffic streams are perturbed temporarily by lane‐changing maneuvers but return to the initial states after relaxations.     

出口道短车道对信号控制交叉口通行能力影响

研究出口道短车道在不同交通条件和道路几何条件下对道路交通能力的影响,可以进一步完善交叉口通行能力计算理论体系,对工程设计给出理论依据。介绍了相关研究背景,交叉口出口道短车道对信号控制交叉口通行能力的修正。最后从短车道长度、有效绿灯时间、路段与进口道饱和流量差、交通流基本参数关系模型等因素,分析了出口道短车道对通行能力的影响程度。     

道路交叉口车道功能划分

对车道功能划分的影响因素作系统性分析。从交叉口交通条件、道路条件、信号控制条件以及上游交通条件等因素对交叉口车道功能合理划分进行研究。     

An Analytical Approach for Estimating the Highway Capacity Manual Signalized Intersection Delay Variability

Abstract: This article developed a generalized model incorporating three stochastic input variables in the Highway Capacity Manual (HCM) delay equation and analyzed the delay variability explicitly considering variations in key input variables including traffic volume, effective green time, and saturation flow rate. An integration method was used for calculations of mean and variance of the HCM delay. Unlike the previous Expectation Function Method, the proposed integration method can be applied for both undersaturated and oversaturated situations. The applicability of the proposed methodology was demonstrated through a hypothetical case study for a lane group at an isolated signalized intersection. The effects of stochastic variables (e.g., traffic volume, saturation flow rate, and effective green time) and correlations among these variables in the HCM delay were examined.     

许可相位下左转车道存储段长度计算

以左转交通量、周期长度、左转绿灯时间、对向交通量为变量,运用交通流理论和排队论,从满足左转排队车辆停车需求的角度,对信号交叉口进口道设置左转许可相位和一条左转专用车道时的左转车道存储段长度展开研究。基于M/M/1排队系统,建立许可相位下单条左转车道存储段长度计算的理论模型。在此基础上,讨论模型的适用条件和实用性,分析存储段长度随饱和度、左转交通量的变化规律,综合考虑空间几何条件、服务质量、经济性能,指出排队车辆数不宜超过20辆,如置信概率为95%,则实用饱和度区间为[0,0.8]。讨论置信概率、设计交通量及单位车辆停放长度等参数的取值方法。对典型情况计算、分析,提出极限交通量、极限排队长度、临界交通量、临界排队长度两组便于工程应用的概念,并绘制图表。制定应用图表确定存储段长度的流程;讨论设计快速校核表的制定和应用。该研究为交叉口采用左转许可相位且进口道仅设置一条左转车道的存储段长度确定提供依据,也可作为左转专用相位的设置依据。     

沪南公路现状拥堵分析及改善对策

对上海沪南公路区域路网,交通流量,交叉口和出入口影响以及现状交通构成进行拥堵分析。在拥堵原因分析基础上,提出了完善区域路网;取消支路交叉口信控,采用右进右出交通组织;增加车道规模,局部路段采用"主路+辅路"的交通组织形式等改善对策。最终指出解决沪南公路交通拥堵问题的最佳策略是增加车道规模,局部路段采用"主路+辅路"的交通组织形式,可满足周围居民出行需求。     

Long‐Distance‐Commuter (LDC) Lane: A New Concept for Freeway Traffic Management

Many freeways connect two major cities (e.g., Gold Coast to Brisbane) in Australia. A great portion of commuters travel between these two cities whereas the number of commuters taking the on‐ramps and off‐ramps in between is comparatively small. Enlightened by this observation, we propose a novel and practical concept for freeway traffic management: long‐distance‐commuter (LDC) lane. The LDC lane is a dedicated lane that only commuters traveling between the two major cities can use. Since there is no or only minor disturbance from forced lane‐changing of vehicles from other lanes, the LDC lane admits a much higher capacity. Our preliminary case study based on the freeway between Gold Coast and Brisbane demonstrates that using the LDC lane significantly increases the average speed as well as overall capacity.     

Modeling adaptive platoon and reservation-based intersection control for connected and autonomous vehicles employing deep reinforcement learning

As a cutting-edge strategy to reduce travel delay and fuel consumption, platooning of connected and autonomous vehicles (CAVs) at signal-free intersections has become increasingly popular in academia. However, when determining optimal platoon size, few studies have attempted to comprehensively consider the relations between the size of a CAV platoon and traffic conditions around an intersection. To this end, this study develops an adaptive platoon-based autonomous intersection control model, named INTEL-PLT, which adopts deep reinforcement learning technique to realize the optimization of multiple dynamic objectives (e.g., efficiency, fairness, and energy saving). The framework of INTEL-PLT has a two-level structure: The first level employs a reservation-based policy integrated with a nonconflicting lane selection mechanism to determine the lanes’ releasing priorities; and the second level uses a deep Q-network algorithm to identify the optimal platoon size based on real-time traffic conditions (e.g., traffic density, vehicle movement, etc.) of an intersection. The model is validated and examined on the simulator Simulation of Urban Mobility. It is found that the proposed model exhibits superior performances on both travel efficiency and fuel conservation as compared with state-of-the-art methods in three typical traffic conditions. Moreover, several in-depth insights learned from the simulations are provided in this paper, which could better explain the relation between platoon size and traffic condition.     

浅谈城市道路交叉口交通组织

在阐述城市道路交叉口交通组织基本要求的基础上,对有无信号灯控制的交叉口设计作了分析,并将导向车道宽度设计、平面交叉口渠化以及平面交叉口标线设置应注意的问题进行了探讨,以使道路交通安全、有序、高效运行。     

Wireless charging utility maximization and intersection control delay minimization framework for electric vehicles

This study presents the Wireless Charging Utility Maximization (WCUM) framework, which aims to maximize the utility of Wireless Charging Units (WCUs) for electric vehicle (EV) charging through the optimal WCU deployment at signalized intersections. Furthermore, the framework aims to minimize the control delay at all signalized intersections of the network. The framework consists of a two‐step optimization formulation, a dynamic traffic assignment model to calculate the user equilibrium, a traffic microsimulator to formulate the objective functions, and a global Mixed Integer Non‐Linear Programming (MINLP) optimization solver. An optimization problem is formulated for each intersection, and another for the entire network. The performance of the WCUM framework is tested using the Sioux Falls network. We perform a comparative study of 12 global MINLP solvers with a case study. Based on solution quality and computation time, we choose the Couenne solver for this framework.     

A Network Generalized Extreme Value Model for Route Choice Allowing Implicit Route Enumeration

This article introduces an adaptation of the Network GEV model for modelling joint choices, named Joint Network GEV (JNG), and its application to the route choice context, named Link‐Based JNG (LB‐JNG), assuming the choice of a route as the joint choice of all links belonging to that route. The LB‐JNG model aims at reproducing the effects of routes overlapping with a theoretical robust framework (since it belongs to the Network GEV, to date the most flexible closed‐form model in reproducing covariances), allowing at the same time for easy application to real networks through a closed‐form probability statement, a proper definition of its parameters and the availability of an implicit route enumeration algorithm for network loading. The article carries out first an overview of the theoretical properties of the JNG model. Then, the LB‐JNG adaptation to route choice is described, and its capability to reproduce the effects of routes overlapping is investigated using some test networks, wherein the performances of the proposed model are also compared with those of other route choice models available in the literature. Finally, an implicit route enumeration algorithm for macroscopic static stochastic network loading, based on a double‐step generalization of Dial's STOCH algorithm, is proposed and tested on real size networks.     

基于交通延误最小的道路养护策略优化

道路养护常常需要关闭相应的机动车道 ,因而会产生新的交通延误。为减少四车道道路养护时所带来的交通延误 ,论文建立了基于交通延误最小的道路养护策略的整数规划优化模型 ,其中目标函数为路网总的交通延误最小 ,约束条件为总的可用工作时间 ;并通过具体的实例对模型进行了验证。在整数规划优化的基础上 ,论文还讨论了通过引入交通标志对交通流进行诱导从而进一步减少交通延误的可能性     

Random Process Model for Urban Traffic Flow Using a Wavelet‐Bayesian Hierarchical Technique

Abstract: The existing well‐known short‐term traffic forecasting algorithms require large traffic flow data sets, including information on current traffic scenarios to predict the future traffic conditions. This article proposes a random process traffic volume model that enables estimation and prediction of traffic volume at sites where such large and continuous data sets of traffic condition related information are unavailable. The proposed model is based on a combination of wavelet analysis (WA) and Bayesian hierarchical methodology (BHM). The average daily “trend” of urban traffic flow observations can be reliably modeled using discrete WA. The remaining fluctuating parts of the traffic volume observations are modeled using BHM. This BHM modeling considers that the variance of the urban traffic flow observations from an intersection vary with the time‐of‐the‐day. A case study has been performed at two busy junctions at the city‐centre of Dublin to validate the effectiveness of the strategy.     

Short‐Term Traffic Speed Prediction for an Urban Corridor

Short‐term traffic speed prediction is one of the most critical components of an intelligent transportation system (ITS). The accurate and real‐time prediction of traffic speeds can support travellers’ route choices and traffic guidance/control. In this article, a support vector machine model (single‐step prediction model) composed of spatial and temporal parameters is proposed. Furthermore, a short‐term traffic speed prediction model is developed based on the single‐step prediction model. To test the accuracy of the proposed short‐term traffic speed prediction model, its application is illustrated using GPS data from taxis in Foshan city, China. The results indicate that the error of the short‐term traffic speed prediction varies from 3.31% to 15.35%. The support vector machine model with spatial‐temporal parameters exhibits good performance compared with an artificial neural network, a k‐nearest neighbor model, a historical data‐based model, and a moving average data‐based model.     

A Cell‐Based Model for Multi‐class Doubly Stochastic Dynamic Traffic Assignment

Abstract: This article proposes a cell‐based multi‐class dynamic traffic assignment problem that considers the random evolution of traffic states. Travelers are assumed to select routes based on perceived effective travel time, where effective travel time is the sum of mean travel time and safety margin. The proposed problem is formulated as a fixed point problem, which includes a Monte–Carlo‐based stochastic cell transmission model to capture the effect of physical queues and the random evolution of traffic states during flow propagation. The fixed point problem is solved by the self‐regulated averaging method. The results illustrate the properties of the problem and the effectiveness of the solution method. The key findings include the following: (1) Reducing perception errors on traffic conditions may not be able to reduce the uncertainty of estimating system performance, (2) Using the self‐regulated averaging method can give a much faster rate of convergence in most test cases compared with using the method of successive averages, (3) The combination of the values of the step size parameters highly affects the speed of convergence, (4) A higher demand, a better information quality, or a higher degree of the risk aversion of drivers can lead to a higher computation time, (5) More driver classes do not necessarily result in a longer computation time, and (6) Computation time can be significantly reduced by using small sample sizes in the early stage of solution processes.     

Spreading Patterns of Malicious Information on Single‐Lane Platooned Traffic in a Connected Environment

The connected vehicle can be easily attacked by cyber threats due to its communication through the wireless network in an open‐access environment. But very few studies have paid attention to the spreading of malicious information such as denial of service, message delay/replay, and eavesdropping generated by cyberattacks. To this end, this article introduces an analytical model, named vehicular malicious information propagation (VMIP), which integrates a classical epidemic model through two‐layer system structure, in which the upper layer describes the malicious information spreading and the lower describes the traffic flow dynamics. The proposed VMIP model is designated for platooned (one‐lane, particularly) traffic. Numerical experiments show the proposed model can efficiently describe the interactions between traffic dynamics and malicious information spreading; and the information propagation highly depends on traffic flow patterns. This article is expected to contribute to a better understanding of the impacts of cyberattacks on traffic and lays a foundation for future development of control strategies on mitigating the disastrous effects of cyberattacks.